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Computer-aided detection tool development for teaching chest radiograph pattern recognition to undergraduate
Sibusiso Mdletshe1, Andre L Nel2, Louise Rainford3
1Department of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Johannesburg, Johannesburg, South Africa.
Computer-aided detection (CAD) tools can enhance undergraduate radiography education by providing structured, authentic, and self-directed learning experiences for chest radiography pattern recognition. Careful design is crucial for effective skill development.
Area of Science:
- Medical imaging education
- Radiography training
- Health professions education
Background:
- Medical imaging (MI) education is evolving with technological advancements, emphasizing radiographers' pattern recognition skills.
- Technology-enhanced learning, including computer-aided detection (CAD) tools, is increasingly used to develop these skills at the undergraduate level.
- Developing context-relevant educational approaches requires careful exploration and planning.
Purpose of the Study:
- To explore the need for and capability of a CAD tool for teaching chest radiography pattern recognition.
- To describe the essential features of a CAD tool for undergraduate radiography programs.
Main Methods:
- Qualitative descriptive design with an interpretive research paradigm.
- Focus group interviews with participants involved in teaching clinical skills to radiography students.
- Verbatim transcription and step-by-step data analysis.
Main Results:
- A structured approach is critical for enhancing implicit skills within CAD tool design.
- An authentic tool simulating real-world image analysis experiences is essential.
- A tool promoting self-directed learning with diverse pathological conditions is ideal.
Conclusions:
- Findings guide radiography educators in designing effective CAD tools for chest radiography pattern recognition.
- The study highlights key considerations for developing impactful educational technology in medical imaging.
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